Mental health of people with multiple sclerosis during the COVID-19 outbreak: A prospective cohort and cross-sectional case-control study of the UK MS Register.

BACKGROUND: People with MS (pwMS) have had higher rates of anxiety and depression than the general population before the COVID-19 pandemic, placing them at higher risk of experiencing poor psychological wellbeing during the pandemic. OBJECTIVE: To assess mental health and its social/lifestyle determinants in pwMS during the first wave of the outbreak in the United Kingdom. METHODS: This is a community-based, prospective longitudinal cohort and cross-sectional case-control online questionnaire study. It includes 2010 pwMS from the UK MS Register and 380 people without MS. RESULTS: The Hospital Anxiety and Depression Scale scores of pwMS for anxiety and depression during the outbreak did not change from the previous year. PwMS were more likely to have anxiety (using General Anxiety Disorder-7) and/or depression (using Patient Health Questionnaire-9) than controls during the outbreak (OR: 2.14, 95% CI: 1.58-2.91). PwMS felt lonelier (OR: 1.37, 95% CI: 1.04-1.80) reported worse social support (OR: 1.90, 95% CI: 1.18-3.07) and reported worsened exercise habits (OR: 1.65, 95% CI: 1.18-2.32) during the outbreak than controls. CONCLUSION: Early in the pandemic, pwMS remained at higher risk of experiencing anxiety and depression than the general population. It is important that multidisciplinary teams improve their support for the wellbeing of pwMS, who are vulnerable to the negative effects of the pandemic on their lifestyle and social support.

Willingness to receive a COVID-19 vaccine in people with multiple sclerosis - UK MS Register survey.

BACKGROUND & METHODS: We conducted an online COVID-19 survey as the vaccines became available, utilising the UK MS Register, to understand people with multiple sclerosis (pwMS) views on COVID-19 vaccination and the subsequent vaccine uptake rates. RESULTS & CONCLUSION: 94.4% of 3191 pwMS surveyed indicated they would get a COVID-19 vaccine, while 5.6% would not. PwMS who have previously had an influenza vaccine, increasing age and the perception of having sufficient information about the vaccine were associated with increased likelihood of getting a vaccine. 51.7% of 3191 pwMS completed a follow-up survey indicating they received at least 1 dose of a COVID-19 vaccine. The proportion having had the vaccination based on their prior opinions was 53.2% in 'Yes' group and 27.0% in 'No' group, the latter reflecting a change based on their initial views. More information on COVID-19 vaccine safety in pwMS would be helpful for people to make informed decisions.

United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers (UK-REACH): a retrospective cohort study using linked routinely collected data, study protocol.

INTRODUCTION: COVID-19 has spread rapidly worldwide, causing significant morbidity and mortality. People from ethnic minorities, particularly those working in healthcare settings, have been disproportionately affected. Current evidence of the association between ethnicity and COVID-19 outcomes in people working in healthcare settings is insufficient to inform plans to address health inequalities. METHODS AND ANALYSIS: This study combines anonymised human resource databases with professional registration and National Health Service data sets to assess associations between ethnicity and COVID-19 diagnosis, hospitalisation and death in healthcare workers in the UK. Adverse COVID-19 outcomes will be assessed between 1 February 2020 (date following first confirmed COVID-19 case in UK) and study end date (31 January 2021), allowing 1-year of follow-up. Planned analyses include multivariable Poisson, logistic and flexible parametric time-to-event regression within each country, adjusting for core predictors, followed by meta-analysis of country-specific results to produce combined effect estimates for the UK. Mediation analysis methods will be explored to examine the direct, indirect and mediated interactive effects between ethnicity, occupational group and COVID-19 outcomes. ETHICS AND DISSEMINATION: Ethical approval for the UK-REACH programme has been obtained via the expedited HRA COVID-19 processes (REC ref: 20/HRA/4718, IRAS ID: 288316). Research information will be anonymised via the Secure Anonymised Information Linkage Databank before release to researchers. Study results will be submitted for publication in an open access peer-reviewed journal and made available on our dedicated website (https://uk-reach.org/). TRIAL REGISTRATION NUMBER: ISRCTN11811602.

Real-time spatial health surveillance: Mapping the UK COVID-19 epidemic.

Introduction The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Objectives The primary objective of this study was to develop a real-time geospatial surveillance system to monitor the spread of COVID-19 across the UK. Methods Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. Results We demonstrate that using a combination of crowd-sourced app data and sophisticated geo-statistical techniques it is possible to predict hot spots of COVID-19 at fine geographic scales, nationally. We are also able to produce estimates of their precision, which is an important pre-requisite to an effective control strategy to guard against over-reaction to potentially spurious features of 'best guess' predictions. Conclusion In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.